• Review of Korean Society for Internet Information
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• v.14 no.1
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• pp.8-28
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• 2013

In a backlash against corporate branding and capitalism, a growing number of consumers are resisting current marketplace practices and big corporate brands. One particular form of this phenomenon is the emergence of anti-brand communities in social media. The current study, which surveyed a sample of 251 anti-brand community members on Facebook, provides a preliminary understanding of the characteristics and antecedents of anti-brand communities as a new platform for consumer empowerment and anti-brand activism. Findings suggest that consumers' engagement in online anti-brand communities, especially through social media, may be triggered by their negative experiences with employees, product quality, post-purchase service, and value/price. They are motivated, the results show, by seven primary factors: altruism, revenge, advice seeking, convenience, sympathy seeking, socialization, and the need to vent.

• Journal of Information Technology Services
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• v.22 no.3
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• pp.141-165
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• 2023

With the advent of the fourth industrial revolution, technologies such as the Internet of Things, artificial intelligence and cloud computing are developing rapidly, and smart homes enabled by these technologies are rapidly gaining popularity. To gain a competitive advantage in the global market, companies must understand the differences in consumer needs in different countries and cultures and develop corresponding business strategies. Therefore, this study conducts a comparative analysis of consumer reviews of smart homes in South Korea and China. This study collected online reviews of SmartThings, ThinQ, Msmarthom, and MiHome, the four most commonly used smart home apps in Korea and China. The collected review data is divided into satisfied reviews and dissatisfied reviews according to the ratings, and topics are extracted for each review dataset using LDA topic modeling. Next, the extracted topics are classified according to five evaluation factors of Perceived Usefulness, Reachability, Interoperability,Trustness, and Product Brand proposed by previous studies. Then, by comparing the importance of each evaluation factor in the two datasets of satisfaction and dissatisfaction, we find out the factors that affect consumer satisfaction and dissatisfaction, and compare the differences between users in Korea and China. We found Trustness and Reachability are very important factors. Finally, through language network analysis, the relationship between dissatisfied factors is analyzed from a more microscopic level, and improvement plans are proposed to the companies according to the analysis results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.89-93
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• 2014

Reviews are very important for potential consumer' making choices. They are also used by manufacturers to find problems of their products and to collect competitors' business information. But someone write fake reviews to mislead readers to make wrong choices. Therefore detecting fake reviews is an important problem for the E-commerce sites. Support Vector Machines (SVMs) are very important text classification algorithms with excellent performance. In this paper, we propose a new incremental algorithm based on weight and the extension of Karush-Kuhn-Tucker(KKT) conditions and Convex Hull for online Review Spam Detection. Finally, we analyze its performance in theory.

• Knowledge Management Research
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• v.23 no.2
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• pp.253-276
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• 2022

Online reviews attract much attention because they play an essential role in consumer decision-making. Therefore, it is necessary to investigate the review attributes that affect the perceived helpfulness of consumers. However, most previous studies on the helpfulness of online reviews mainly focus on quantitative factors such as review volume and reviewer attributes. Recently, some studies have investigated the impact of review content and linguistic style matching on consumers' purchase decision-making. Those studies show that consumers consider additional review attributes when evaluating reviews in decision-making. To fill the research gap with existing literature, we investigated the impact of review content and linguistic style matching on review helpfulness. Moreover, this study investigated how the reviewers' expertise moderates the effect of the review content and linguistic style matching on the review helpfulness. The empirical results show that positive affective content has a negative effect on the review helpfulness. The negative affective content and linguistic style matching positively affect review helpfulness. Review expertise relieved the impact of negative affective content and linguistic style matching on review helpfulness. According to the mechanism confirmed in this study, online e-commerce companies can achieve corporate sales growth by identifying factors affecting review helpfulness and reflecting them in their marketing strategies.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.316-330
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• 2020

The study analyzes reviews of hardware products, customer service products, and products that take the form of a convergence of hardware and cloud services in ICT using text mining. We derive keywords of each review and find the differentiation of words that are used to derive topics. A cluster analysis is performed to categorize reviews into their respective clusters. Through this study, we observed which keywords are most often used for each product type and found topics that express the characteristics of products and services using topic modeling. We derived keywords such as "professional" and "technician" which are topics that suggest the excellence of the service provider in the review of service products. Further, we identified adjectives with positive connotations such as "favorite", "fine", "fun", "nice", "smart", "unlimited", and "useful" from Amazon Eco review, an integrated product and service. Using the cluster analysis, the entire review was clustered into three groups, and three product type reviews exclusively resulted in belonging to each different cluster. The study analyzed the differences whereby consumer needs are expressed differently in reviews depending on the type of product and suggested that it is necessary to differentiate product planning and marketing promotion according to the product type in practice.

• Management & Information Systems Review
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• v.30 no.1
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• pp.159-185
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• 2011

We can divide brand experience in the brand community of online blog into the following five types: sensuous experience, emotional experience, cognitive experience, behavioral experience, and relational experience. And this study is aimed at looking into what differences are among the effects those five have on the consumer-brand relationship. Also we wanted to analyse empirically what structural relations this consumer-brand relationship through the whole experience has with brand attachment and brand commitment. The outcome shows that emotional experience, cognitive experience and relational experience affect the consumer-brand relationship but sensuous experience and behavioral experience. And our analysis of what structural relations the consumer-brand relationship through brand experience has with brand attachment and brand commitment revealed that the consumer-brand relationship through brand experience has a direct effect on brand attachment but it doesn't have on brand commitment. Brand commitment was confirmed to be affected only through brand attachment. Finally, this is in agreement with the result of the precedent study that brand commitment is an effect variable of brand attachment.

• Journal of Family Resource Management and Policy Review
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• v.11 no.4
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• pp.21-36
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• 2007

As online shopping is expanding rapidly, the damages undergone by consumers are also dramatically increasing. This research mainly focused on the damages experienced through Internet shopping. The purpose of this study was to develop a standardized scale to measure damages sustained through an Internet shopping mall. A preliminary 35-item scale was developed through a literature review, and 1,230 consumers responded to an online survey using the preliminary scale. This research was supported by the surveys conducted on consumers who had previously shopped at an Internet fashion mall. This research was conducted with the intention of not only supplying academic data on the damage sustained by consumers, but also understanding the consumers' basic behavior patterns. Then a series of tests, such as test-retest, item-to-total correlation, Cron bach's reliability coefficient and factor analysis, were conducted using the survey data and a final scale with 26-items was constructed in the end. The damage sustained in Internet shopping malls scale for consumers consisted of three factors: 1. Trouble with safety 2. Trouble with payment and delivery; and 3. Trouble with after-sales services.

• Journal of Fashion Business
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• v.22 no.3
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• pp.39-56
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• 2018

Since trusting in other consumers may refer to having similar needs and preferences on fashion goods with them, interpersonal trust can be a reliable and practical criterion for market segmentation online. Therefore, this study aims to identify fashion online consumers based on interpersonal trust. This study segments fashion consumers based on interpersonal trust and experience and describes characteristics of each segment by examining demo-psychographic and behavioral variables as well as clothing consumption values. An online survey was conducted to collect data from 426 adult consumers who had bought fashion goods from their patronized e-tailer in the past one month. They completed a self-administered questionnaire inquiring about interpersonal trust, trust in e-tailers, purchase intentions, clothing consumption values, and their purchasing behavior online. Two-step cluster analysis generated four segments: distrustful doers, trusting doers, inactive trusters, and distrusters. They exhibited different characteristics in gender, online experiences, interpersonal trust, clothing consumption values, trust in the e-tailers, and attitude toward the e-tailers. Providing a new effective segmentation base, this study suggests that fashion marketers identify customers with a high level of trust in other customers and develop an encouraging environment that customers can interact with others in order to increase the effectiveness of trust. Because customers with a higher level of interpersonal trust are likely to have stronger trust in e-tailers with, more favorable attitude and purchase intention, and highly perceive the value of clothing consumption than those who have a lower level of interpersonal trust.

• The Journal of Industrial Distribution & Business
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• v.11 no.8
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• pp.7-19
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• 2020

Purpose: Prior studies rarely investigated the effects of the Word of Mouse (WoM) information on consumers' motivation and willingness to purchase a product. Furthermore, few scholars have studied how word-of-mouth information works and they fail to find consistent results. Research design, data and methodology: This study uses a multivariate regression model to investigate the influence of WoM on consumer attitudes and consumer decision-making. It categorizes the quality of WoM into source level and acceptance level, to analyze its influence from a new perspective. A total of 400 surveys were completed, resulting in 336 usable questionnaires for analysis. It was collected in 14 cities from all regions in China. This study constructs a theoretical model of WoM influence on consumers' purchase willingness based on a systematic review of the related literature on WoM quality, perceived value, customer trust, and consumers' purchase willingness. Results: Empirical results reveal that the Internet WoM (consumer's source level and acceptance level) indirectly affects consumer behavior by influencing consumer attitudes. Conclusions: This study provides practical significance and value for merchants to develop better WoM marketing and to establish the reliability of WoM websites. Companies should consider online WoM from the perspective of consumers, thereby improving existing marketing strategies.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.191-205
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• 2012

A book review is one of the most important sources of information which provide the descriptive and evaluative contents about books. Reviews have great influence on consumer behavior because they are believed to be more reliable than information provided by sellers. Readers who read a book review includes information about book decide whether they will buy or not. This study examines customer attitude change by book reviews with regarding to different type of information sources(experts and prior customers) and different directions of messages. We address the following research questions: (1) Can positive book reviews with credibility have a positive impact on acceptance of books? (2) Can negative book reviews with credibility have a negative impact on acceptance of books? The results shows that a credibility is an essential factor for affecting customers' mind. When positive book reviews were written, both expert and customer opinions have a positive impact on acceptance of customers. Given negative book reviews of experts, trustworthiness is more important than expertise. However, a objectivity of customer's reviews is more important.